In the ACF(nlme) the normalization of the numerator has been done by N and I want to normalize it by N-k, where N is the observations and k is the lag.
Baloo --- On Tue, 12/22/09, ONKELINX, Thierry <thierry.onkel...@inbo.be> wrote: From: ONKELINX, Thierry <thierry.onkel...@inbo.be> Subject: RE: [R] Nested For loops To: "baloo mia" <baloo_...@yahoo.com>, r-help@r-project.org Date: Tuesday, December 22, 2009, 1:00 AM Baloo, Why don't you use the built-in acf function? Thierry ---------------------------------------------------------------------------- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek team Biometrie & Kwaliteitszorg Gaverstraat 4 9500 Geraardsbergen Belgium Research Institute for Nature and Forest team Biometrics & Quality Assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 thierry.onkel...@inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens baloo mia Verzonden: dinsdag 22 december 2009 2:07 Aan: r-help@r-project.org Onderwerp: [R] Nested For loops Dear R experts, Might be very simple question to ask but would be insightful. As the same story of nested "for loops". following is the code that I am using to get the autocorrelation function of the sample data. I have tried to get rid of for loops but since I am touching R after such a long time that I need to practice more but I need help to revive my skills. I know that apply() or sapply() would be beneficial. I need help... Best Wishes, Baloo R code ---------- acf_wal <- function (infile) { data<-read.table(infile) data_value <- data[,-1] data_value_mean <- mean(data_value) data_value_square <- (data_value - data_value_mean) ^ 2 square_sum<-sum(data_value_square) entry<-NROW(data_value) deno<-square_sum/entry tab1<-c() tab2<-c() ps_value <- seq(0,(floor(entry/2)),1) for(k in 0:(floor(entry/2))){ for (i in 1:(entry-k)) { mult<-(data_value[i] - data_value_mean) * (data_value [i+k] - data_value_mean) tab1 <- c(tab1,mult) } auto_avg<-mean(tab1) tab1<-c() auto_corr<-auto_avg/deno tab2<-c(tab2,auto_corr) } table_value <- cbind (ps_value, tab2) colnames(table_value) <- c("#ps", "acf") outfile<-unlist(strsplit(infile, split=".", fixed=TRUE))[1] write.table(table_value,file=paste(outfile,"acf.dat",sep="-"),row.names=FALSE,sep="\t",quote=F) } -------------- Sample data ------------------ 1 16.0071 2 16.7966 3 17.575 4 18.1614 5 15.982 6 16.8515 7 15.6828 8 14.9652 9 14.8623 10 14.7079 -------------------- Help in this regard would be highly appreciated. [[alternative HTML version deleted]] Druk dit bericht a.u.b. niet onnodig af. Please do not print this message unnecessarily. Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
